Support group_over
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- Python
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Description
Multi-dimensional grouped operations should be relatively straightforward -- the main complexity will be writing an N-dimensional concat that doesn't involve repetitively copying data.
The idea with group_over would be to support groupby operations that act on a single element from each of the given groups, rather than the unique values. For example, ds.group_over(['lat', 'lon']) would let you iterate over or apply to 2D slices of ds, no matter how many dimensions it has.
Roughly speaking (it's a little more complex for the case of non-dimension variables), ds.group_over(dims) would get translated into ds.groupby([d for d in ds.dims if d not in dims]).
Related: #266
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the existing groupby implementation and the discussion in related issue #266; this issue names no files or tests. Done would mean supporting group_over for multidimensional grouped operations, including the required N-dimensional concatenation behavior and non-dimension variables.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100